Building management system with semantic model integration

ABSTRACT

A building management system (BMS) includes memory devices having instructions stored thereon that, when executed by processors, cause the processors to perform operations including obtaining a BMS ontology data model defining a plurality of BMS model classes and relationships between the BMS model classes, obtaining a plurality of BMS object definitions including equipment definitions defining a plurality of different types of equipment and point definitions defining a plurality of different types of points, assigning a BMS model class selected from the plurality of BMS model classes to each of the plurality of BMS object definitions, generating a semantic site model by classifying a plurality of BMS objects associated with a building site according to the BMS object definitions and the BMS model classes assigned thereto, and controlling building equipment using the semantic site model.

BACKGROUND

The present disclosure relates generally to the field of buildingmanagement systems (BMSs), and more particularly to standardizing a BMSusing a semantic model. A BMS is, in general, a system of devicesconfigured to control, monitor, and manage equipment in or around abuilding. A BMS can include, for example, a HVAC system, a securitysystem, a lighting system, a fire alerting system, any other system thatis capable of managing building functions or devices, or any combinationthereof. Equipment, spaces, and points associated with the BMS can berepresented as objects in a BMS configuration dataset. To facilitateuser interaction with a BMS, it may be desirable to map BMS objects toan ontology data model such that the BMS objects and objectrelationships are described in a semantic or natural manner.

SUMMARY

One embodiment of the present disclosure is a building management system(BMS). The BMS includes one or more memory devices having instructionsstored thereon that, when executed by one or more processors, cause theone or more processors to perform operations including obtaining a BMSontology data model defining a plurality of BMS model classes andrelationships between the BMS model classes, obtaining a plurality ofBMS object definitions including equipment definitions defining aplurality of different types of equipment and point definitions defininga plurality of different types of points, assigning a BMS model class toeach of the plurality of BMS object definitions, where the BMS modelclass is a semantic identifier selected from the plurality of BMS modelclasses defined by the BMS ontology data model, generating a semanticsite model by classifying a plurality of BMS objects associated with abuilding site according to the BMS object definitions and the BMS modelclasses assigned thereto, and controlling building equipment using thesemantic site model.

In some embodiments, the operations further include receiving a userinput indicating one or more user-defined object identifiers associatedwith a first BMS object definition of the plurality of BMS objectdefinitions. In some embodiments, classifying the plurality of BMSobject includes identifying a subset of the plurality of BMS objectsthat satisfy at least one of the user-defined object identifiers andclassifying the subset of the plurality of BMS object as the BMS modelclass assigned to the first BMS object definition.

In some embodiments, the operations further include analyzingconfiguration data for the BMS to identify a subset of the plurality ofBMS objects that satisfy each of the plurality of BMS objectdefinitions. In some embodiments, each of the plurality of BMS objectsare classified as the BMS model class assigned to a corresponding BMSobject definition.

In some embodiments, assigning the BMS model class to each of theplurality of BMS object definitions further includes receiving a userselection of the BMS model class for each of the BMS object definitionsand assigning the BMS model class to each of the plurality of BMS objectdefinitions based on the user selection.

In some embodiments, the BMS objects associated with the building siteinclude at least one of equipment objects representing specific buildingequipment and point objects representing specific points in the BMS.

In some embodiments, the BMS objects associated with the building siteinclude space objects representing specific spaces in the building siteand where the plurality of BMS object definitions further include spacedefinitions defining a plurality of different spaces.

In some embodiments, the operations further include obtaining a faultdetection rule for the building site, the fault detection rule includingone or more fault criteria defined without reference to one or moreparticular BMS objects needed to evaluate the fault criteria, using thesemantic site model to identify the particular BMS objects needed toevaluate the fault criteria, and detecting a fault condition byevaluating the one or more fault criteria using data associated with theparticular BMS objects.

In some embodiments, evaluating the fault criteria includes comparing avalue provided by one or more of the particular BMS objects against athreshold.

Another embodiment of the present disclosure is a method includingobtaining a BMS ontology data model defining a plurality of buildingmanagement system (BMS) model classes and relationships between the BMSmodel classes, obtaining a plurality of BMS object definitions includingequipment definitions defining a plurality of different types ofequipment and point definitions defining a plurality of different typesof points, assigning a BMS model class to each of the plurality of BMSobject definitions, where the BMS model class is a semantic identifierselected from the plurality of BMS model classes defined by the BMSontology data model, generating a semantic site model by classifying aplurality of BMS objects associated with a building site according tothe BMS object definitions and the BMS model classes assigned thereto,and controlling building equipment using the semantic site model.

In some embodiments, the method further includes receiving a user inputindicating one or more user-defined object identifiers associated with afirst BMS object definition of the plurality of BMS object definitions.In some embodiments, classifying the plurality of BMS object includesidentifying a subset of the plurality of BMS objects that satisfy atleast one of the user-defined object identifiers and classifying thesubset of the plurality of BMS object as the BMS model classcorresponding to the first BMS object definition.

In some embodiments, the method further includes analyzing configurationdata for the BMS to identify a subset of the plurality of BMS objectsthat satisfy each of the plurality of BMS object definitions. In someembodiments, each of the plurality of BMS objects are classified as theBMS model class assigned to a corresponding BMS object definition.

In some embodiments, assigning the BMS model class to each of theplurality of BMS object definitions further includes receiving a userselection of the BMS model class for each of the BMS object definitionsand assigning the BMS model class to each of the plurality of BMS objectdefinitions based on the user selection.

In some embodiments, the BMS objects associated with the building siteinclude at least one of equipment objects representing instances ofbuilding equipment and point objects representing specific points in theBMS.

In some embodiments, the BMS objects associated with the building siteinclude space objects representing specific spaces in the building siteand where the plurality of BMS object definitions further include spacedefinitions defining a plurality of different spaces.

In some embodiments, the method further includes determining one or morefault detection rules for the building site, detecting a triggercondition based on the one or more fault detection rules, the triggercondition indicating a fault and a first BMS object associated with thefault, and identifying one or more additional BMS objects associatedwith the fault based on the semantic data model.

In some embodiments, the trigger condition includes an indication thatone or more parameters associated with the first BMS object exceed athreshold.

In some embodiments, determining one or more additional BMS objectsassociated with the fault includes identifying a BMS model classassociated with the first BMS object and identifying the one or moreadditional BMS objects based on the relationships between the BMS modelclasses.

Yet another embodiment of the present disclosure is a buildingmanagement system (BMS). The BMS includes one or more memory deviceshaving instructions stored thereon that, when executed by one or moreprocessors, cause the one or more processors to perform operationsincluding generating a semantic site model by classifying a plurality ofBMS objects associated with a building site according to a plurality ofBMS object definitions, each BMS object definition including anequipment definition defining a type of equipment and at least one pointdefinition defining a type of point, where each BMS object definition isassigned a BMS model class selected from a BMS ontology data model,obtaining a fault detection rule for the building site, the faultdetection rule including one or more fault criteria defined withoutreference to one or more particular BMS objects needed to evaluate thefault criteria, using the semantic site model to identify the particularBMS objects needed to evaluate the fault criteria, detecting a faultcondition by evaluating the one or more fault criteria using dataassociated with the particular BMS objects, and initiating an automatedcorrective action in response to detecting the fault condition.

In some embodiments, the operations further include obtaining the BMSontology data model defining a plurality of BMS model classes andrelationships between the BMS model classes, where the BMS model classesare semantic identifiers selected from the plurality of BMS modelclasses defined by the BMS ontology data model.

In some embodiments, the BMS objects associated with the building siteinclude space objects representing specific spaces in the building siteand where the plurality of BMS object definitions further include spacedefinitions defining a plurality of different spaces

BRIEF DESCRIPTION OF THE DRAWINGS

Various objects, aspects, features, and advantages of the disclosurewill become more apparent and better understood by referring to thedetailed description taken in conjunction with the accompanyingdrawings, in which like reference characters identify correspondingelements throughout. In the drawings, like reference numbers generallyindicate identical, functionally similar, and/or structurally similarelements.

FIG. 1 is a drawing of a building equipped with a HVAC system, accordingto some embodiments.

FIG. 2 is a block diagram of a waterside system that may be used inconjunction with the building of FIG. 1, according to some embodiments.

FIG. 3 is a block diagram of an airside system that may be used inconjunction with the building of FIG. 1, according to some embodiments.

FIG. 4 is a block diagram of a building management system (BMS) that maybe used to monitor and/or control the building of FIG. 1, according tosome embodiments.

FIG. 5 is a block diagram of another BMS which can be used to monitorand control the building of FIG. 1, according to some embodiments.

FIG. 6 is a block diagram of a semantic modeling system, according tosome embodiments.

FIGS. 7A and 7B are block diagrams of a semantic modeling architecture,according to some embodiments.

FIG. 8 is a flowchart of a process for generating a semantic site model,according to some embodiments.

FIG. 9 is a flowchart of a process for fault detection and diagnosticsusing a semantic site model, according to some embodiments.

FIGS. 10A-10C show an example interface for viewing and modifying BMSobject definitions, according to some embodiments.

FIGS. 11A-11B show an example interface for defining a selecting a modelclass for a BMS object definition, according to some embodiments.

DETAILED DESCRIPTION

Building HVAC Systems and Building Management Systems

Referring now to FIGS. 1-5, several building management systems (BMS)and HVAC systems in which the systems and methods of the presentdisclosure can be implemented are shown, according to some embodiments.In brief overview, FIG. 1 shows a building 10 equipped with a HVACsystem 100. FIG. 2 is a block diagram of a waterside system 200 whichcan be used to serve building 10. FIG. 3 is a block diagram of anairside system 300 which can be used to serve building 10. FIG. 4 is ablock diagram of a BMS which can be used to monitor and control building10. FIG. 5 is a block diagram of another BMS which can be used tomonitor and control building 10.

Referring particularly to FIG. 1, a perspective view of a building 10 isshown. Building 10 is served by a BMS. A BMS is, in general, a system ofdevices configured to control, monitor, and manage equipment in oraround a building or building area. A BMS can include, for example, aHVAC system, a security system, a lighting system, a fire safety system,any other system that is capable of managing building functions ordevices, or any combination thereof.

The BMS that serves building 10 includes an HVAC system 100. HVAC system100 can include a plurality of HVAC devices (e.g., heaters, chillers,air handling units, pumps, fans, thermal energy storage, etc.)configured to provide heating, cooling, ventilation, or other servicesfor building 10. For example, HVAC system 100 is shown to include awaterside system 120 and an airside system 130. Waterside system 120 canprovide a heated or chilled fluid to an air handling unit of airsidesystem 130. Airside system 130 can use the heated or chilled fluid toheat or cool an airflow provided to building 10. An exemplary watersidesystem and airside system which can be used in HVAC system 100 aredescribed in greater detail with reference to FIGS. 2-3.

HVAC system 100 is shown to include a chiller 102, a boiler 104, and arooftop air handling unit (AHU) 106. Waterside system 120 can use boiler104 and chiller 102 to heat or cool a working fluid (e.g., water,glycol, etc.) and can circulate the working fluid to AHU 106. In variousembodiments, the HVAC devices of waterside system 120 can be located inor around building 10 (as shown in FIG. 1) or at an offsite locationsuch as a central plant (e.g., a chiller plant, a steam plant, a heatplant, etc.). The working fluid can be heated in boiler 104 or cooled inchiller 102, depending on whether heating or cooling is required inbuilding 10. Boiler 104 can add heat to the circulated fluid, forexample, by burning a combustible material (e.g., natural gas) or usingan electric heating element. Chiller 102 can place the circulated fluidin a heat exchange relationship with another fluid (e.g., a refrigerant)in a heat exchanger (e.g., an evaporator) to absorb heat from thecirculated fluid. The working fluid from chiller 102 and/or boiler 104can be transported to AHU 106 via piping 108.

AHU 106 can place the working fluid in a heat exchange relationship withan airflow passing through AHU 106 (e.g., via one or more stages ofcooling coils and/or heating coils). The airflow can be, for example,outside air, return air from within building 10, or a combination ofboth. AHU 106 can transfer heat between the airflow and the workingfluid to provide heating or cooling for the airflow. For example, AHU106 can include one or more fans or blowers configured to pass theairflow over or through a heat exchanger containing the working fluid.The working fluid can then return to chiller 102 or boiler 104 viapiping 110.

Airside system 130 can deliver the airflow supplied by AHU 106 (i.e.,the supply airflow) to building 10 via air supply ducts 112 and canprovide return air from building 10 to AHU 106 via air return ducts 114.In some embodiments, airside system 130 includes multiple variable airvolume (VAV) units 116. For example, airside system 130 is shown toinclude a separate VAV unit 116 on each floor or zone of building 10.VAV units 116 can include dampers or other flow control elements thatcan be operated to control an amount of the supply airflow provided toindividual zones of building 10. In other embodiments, airside system130 delivers the supply airflow into one or more zones of building 10(e.g., via supply ducts 112) without using intermediate VAV units 116 orother flow control elements. AHU 106 can include various sensors (e.g.,temperature sensors, pressure sensors, etc.) configured to measureattributes of the supply airflow. AHU 106 can receive input from sensorslocated within AHU 106 and/or within the building zone and can adjustthe flow rate, temperature, or other attributes of the supply airflowthrough AHU 106 to achieve setpoint conditions for the building zone.

In FIG. 2, waterside system 200 is shown as a central plant having aplurality of subplants 202-212. Subplants 202-212 are shown to include aheater subplant 202, a heat recovery chiller subplant 204, a chillersubplant 206, a cooling tower subplant 208, a hot thermal energy storage(TES) subplant 210, and a cold thermal energy storage (TES) subplant212. Subplants 202-212 consume resources (e.g., water, natural gas,electricity, etc.) from utilities to serve the thermal energy loads(e.g., hot water, cold water, heating, cooling, etc.) of a building orcampus. For example, heater subplant 202 may be configured to heat waterin a hot water loop 214 that circulates the hot water between heatersubplant 202 and building 10. Chiller subplant 206 may be configured tochill water in a cold water loop 216 that circulates the cold waterbetween chiller subplant 206 building 10. Heat recovery chiller subplant204 may be configured to transfer heat from cold water loop 216 to hotwater loop 214 to provide additional heating for the hot water andadditional cooling for the cold water. Condenser water loop 218 mayabsorb heat from the cold water in chiller subplant 206 and reject theabsorbed heat in cooling tower subplant 208 or transfer the absorbedheat to hot water loop 214. Hot TES subplant 210 and cold TES subplant212 may store hot and cold thermal energy, respectively, for subsequentuse.

Hot water loop 214 and cold water loop 216 may deliver the heated and/orchilled water to air handlers located on the rooftop of building 10(e.g., AHU 106) or to individual floors or zones of building 10 (e.g.,VAV units 116). The air handlers push air past heat exchangers (e.g.,heating coils or cooling coils) through which the water flows to provideheating or cooling for the air. The heated or cooled air may bedelivered to individual zones of building 10 to serve the thermal energyloads of building 10. The water then returns to subplants 202-212 toreceive further heating or cooling.

Although subplants 202-212 are shown and described as heating andcooling water for circulation to a building, it is understood that anyother type of working fluid (e.g., glycol, CO2, etc.) may be used inplace of or in addition to water to serve the thermal energy loads. Inother embodiments, subplants 202-212 may provide heating and/or coolingdirectly to the building or campus without requiring an intermediateheat transfer fluid. These and other variations to waterside system 200are within the teachings of the present invention.

Each of subplants 202-212 may include a variety of equipment configuredto facilitate the functions of the subplant. For example, heatersubplant 202 is shown to include a plurality of heating elements 220(e.g., boilers, electric heaters, etc.) configured to add heat to thehot water in hot water loop 214. Heater subplant 202 is also shown toinclude several pumps 222 and 224 configured to circulate the hot waterin hot water loop 214 and to control the flow rate of the hot waterthrough individual heating elements 220. Chiller subplant 206 is shownto include a plurality of chillers 232 configured to remove heat fromthe cold water in cold water loop 216. Chiller subplant 206 is alsoshown to include several pumps 234 and 236 configured to circulate thecold water in cold water loop 216 and to control the flow rate of thecold water through individual chillers 232.

Heat recovery chiller subplant 204 is shown to include a plurality ofheat recovery heat exchangers 226 (e.g., refrigeration circuits)configured to transfer heat from cold water loop 216 to hot water loop214. Heat recovery chiller subplant 204 is also shown to include severalpumps 228 and 230 configured to circulate the hot water and/or coldwater through heat recovery heat exchangers 226 and to control the flowrate of the water through individual heat recovery heat exchangers 226.Cooling tower subplant 208 is shown to include a plurality of coolingtowers 238 configured to remove heat from the condenser water incondenser water loop 218. Cooling tower subplant 208 is also shown toinclude several pumps 240 configured to circulate the condenser water incondenser water loop 218 and to control the flow rate of the condenserwater through individual cooling towers 238.

Hot TES subplant 210 is shown to include a hot TES tank 242 configuredto store the hot water for later use. Hot TES subplant 210 may alsoinclude one or more pumps or valves configured to control the flow rateof the hot water into or out of hot TES tank 242. Cold TES subplant 212is shown to include cold TES tanks 244 configured to store the coldwater for later use. Cold TES subplant 212 may also include one or morepumps or valves configured to control the flow rate of the cold waterinto or out of cold TES tanks 244.

In some embodiments, one or more of the pumps in waterside system 200(e.g., pumps 222, 224, 228, 230, 234, 236, and/or 240) or pipelines inwaterside system 200 include an isolation valve associated therewith.Isolation valves may be integrated with the pumps or positioned upstreamor downstream of the pumps to control the fluid flows in watersidesystem 200. In various embodiments, waterside system 200 may includemore, fewer, or different types of devices and/or subplants Based on theparticular configuration of waterside system 200 and the types of loadsserved by waterside system 200.

Referring now to FIG. 3, a block diagram of an airside system 300 isshown, according to some embodiments. In various embodiments, airsidesystem 300 may supplement or replace airside system 130 in HVAC system100 or may be implemented separate from HVAC system 100. Whenimplemented in HVAC system 100, airside system 300 may include a subsetof the HVAC devices in HVAC system 100 (e.g., AHU 106, VAV units 116,ducts 112-114, fans, dampers, etc.) and may be located in or aroundbuilding 10. Airside system 300 may operate to heat or cool an airflowprovided to building 10 using a heated or chilled fluid provided bywaterside system 200.

In FIG. 3, airside system 300 is shown to include an economizer-type airhandling unit (AHU) 302. Economizer-type AHUs vary the amount of outsideair and return air used by the air handling unit for heating or cooling.For example, AHU 302 may receive return air 304 from building zone 306via return air duct 308 and may deliver supply air 310 to building zone306 via supply air duct 312. In some embodiments, AHU 302 is a rooftopunit located on the roof of building 10 (e.g., AHU 106 as shown inFIG. 1) or otherwise positioned to receive both return air 304 andoutside air 314. AHU 302 may be configured to operate exhaust air damper316, mixing damper 318, and outside air damper 320 to control an amountof outside air 314 and return air 304 that combine to form supply air310. Any return air 304 that does not pass through mixing damper 318 maybe exhausted from AHU 302 through exhaust damper 316 as exhaust air 322.

Each of dampers 316-320 may be operated by an actuator. For example,exhaust air damper 316 may be operated by actuator 324, mixing damper318 may be operated by actuator 326, and outside air damper 320 may beoperated by actuator 328. Actuators 324-328 may communicate with an AHUcontroller 330 via a communications link 332. Actuators 324-328 mayreceive control signals from AHU controller 330 and may provide feedbacksignals to AHU controller 330. Feedback signals may include, forexample, an indication of a current actuator or damper position, anamount of torque or force exerted by the actuator, diagnosticinformation (e.g., results of diagnostic tests performed by actuators324-328), status information, commissioning information, configurationsettings, calibration data, and/or other types of information or datathat may be collected, stored, or used by actuators 324-328. AHUcontroller 330 may be an economizer controller configured to use one ormore control algorithms (e.g., state-Based algorithms, extremum seekingcontrol (ESC) algorithms, proportional-integral (PI) control algorithms,proportional-integral-derivative (PID) control algorithms, modelpredictive control (MPC) algorithms, feedback control algorithms, etc.)to control actuators 324-328.

Still referring to FIG. 3, AHU 302 is shown to include a cooling coil334, a heating coil 336, and a fan 338 positioned within supply air duct312. Fan 338 may be configured to force supply air 310 through coolingcoil 334 and/or heating coil 336 and provide supply air 310 to buildingzone 306. AHU controller 330 may communicate with fan 338 viacommunications link 340 to control a flow rate of supply air 310. Insome embodiments, AHU controller 330 controls an amount of heating orcooling applied to supply air 310 by modulating a speed of fan 338.

Cooling coil 334 may receive a chilled fluid from waterside system 200(e.g., from cold water loop 216) via piping 342 and may return thechilled fluid to waterside system 200 via piping 344. Valve 346 may bepositioned along piping 342 or piping 344 to control a flow rate of thechilled fluid through cooling coil 334. In some embodiments, coolingcoil 334 includes multiple stages of cooling coils that can beindependently activated and deactivated (e.g., by AHU controller 330, byBMS controller 366, etc.) to modulate an amount of cooling applied tosupply air 310.

Heating coil 336 may receive a heated fluid from waterside system 200(e.g., from hot water loop 214) via piping 348 and may return the heatedfluid to waterside system 200 via piping 350. Valve 352 may bepositioned along piping 348 or piping 350 to control a flow rate of theheated fluid through heating coil 336. In some embodiments, heating coil336 includes multiple stages of heating coils that can be independentlyactivated and deactivated (e.g., by AHU controller 330, by BMScontroller 366, etc.) to modulate an amount of heating applied to supplyair 310.

Each of valves 346 and 352 may be controlled by an actuator. Forexample, valve 346 may be controlled by actuator 354 and valve 352 maybe controlled by actuator 356. Actuators 354-356 may communicate withAHU controller 330 via communications links 358-360. Actuators 354-356may receive control signals from AHU controller 330 and may providefeedback signals to controller 330. In some embodiments, AHU controller330 receives a measurement of the supply air temperature from atemperature sensor 362 positioned in supply air duct 312 (e.g.,downstream of cooling coil 334 and/or heating coil 336). AHU controller330 may also receive a measurement of the temperature of building zone306 from a temperature sensor 364 located in building zone 306.

In some embodiments, AHU controller 330 operates valves 346 and 352 viaactuators 354-356 to modulate an amount of heating or cooling providedto supply air 310 (e.g., to achieve a setpoint temperature for supplyair 310 or to maintain the temperature of supply air 310 within asetpoint temperature range). The positions of valves 346 and 352 affectthe amount of heating or cooling provided to supply air 310 by coolingcoil 334 or heating coil 336 and may correlate with the amount of energyconsumed to achieve a desired supply air temperature. AHU controller 330may control the temperature of supply air 310 and/or building zone 306by activating or deactivating coils 334-336, adjusting a speed of fan338, or a combination of both.

Still referring to FIG. 3, airside system 300 is shown to include abuilding management system (BMS) controller 366 and a client device 368.BMS controller 366 may include one or more computer systems (e.g.,servers, supervisory controllers, subsystem controllers, etc.) thatserve as system level controllers, application or data servers, headnodes, or master controllers for airside system 300, waterside system200, HVAC system 100, and/or other controllable systems that servebuilding 10. BMS controller 366 may communicate with multiple downstreambuilding systems or subsystems (e.g., HVAC system 100, a securitysystem, a lighting system, waterside system 200, etc.) via acommunications link 370 according to like or disparate protocols (e.g.,LON, BACnet, etc.). In various embodiments, AHU controller 330 and BMScontroller 366 may be separate (as shown in FIG. 3) or integrated. In anintegrated implementation, AHU controller 330 may be a software moduleconfigured for execution by a processor of BMS controller 366.

In some embodiments, AHU controller 330 receives information from BMScontroller 366 (e.g., commands, setpoints, operating boundaries, etc.)and provides information to BMS controller 366 (e.g., temperaturemeasurements, valve or actuator positions, operating statuses,diagnostics, etc.). For example, AHU controller 330 may provide BMScontroller 366 with temperature measurements from temperature sensors362-364, equipment on/off states, equipment operating capacities, and/orany other information that can be used by BMS controller 366 to monitoror control a variable state or condition within building zone 306.

Client device 368 may include one or more human-machine interfaces orclient interfaces (e.g., graphical user interfaces, reportinginterfaces, text-Based computer interfaces, client-facing web services,web servers that provide pages to web clients, etc.) for controlling,viewing, or otherwise interacting with HVAC system 100, its subsystems,and/or devices. Client device 368 may be a computer workstation, aclient terminal, a remote or local interface, or any other type of userinterface device. Client device 368 may be a stationary terminal or amobile device. For example, client device 368 may be a desktop computer,a computer server with a user interface, a laptop computer, a tablet, asmartphone, a PDA, or any other type of mobile or non-mobile device.Client device 368 may communicate with BMS controller 366 and/or AHUcontroller 330 via communications link 372.

Referring now to FIG. 4, a block diagram of a building management system(BMS) 400 is shown, according to some embodiments. BMS 400 may beimplemented in building 10 to automatically monitor and control variousbuilding functions. BMS 400 is shown to include BMS controller 366 and aplurality of building subsystems 428. Building subsystems 428 are shownto include a building electrical subsystem 434, an informationcommunication technology (ICT) subsystem 436, a security subsystem 438,a HVAC subsystem 440, a lighting subsystem 442, a lift/escalatorssubsystem 432, and a fire safety subsystem 430. In various embodiments,building subsystems 428 can include fewer, additional, or alternativesubsystems. For example, building subsystems 428 may also oralternatively include a refrigeration subsystem, an advertising orsignage subsystem, a cooking subsystem, a vending subsystem, a printeror copy service subsystem, or any other type of building subsystem thatuses controllable equipment and/or sensors to monitor or controlbuilding 10. In some embodiments, building subsystems 428 includewaterside system 200 and/or airside system 300, as described withreference to FIGS. 2-3.

Each of building subsystems 428 may include any number of devices,controllers, and connections for completing its individual functions andcontrol activities. HVAC subsystem 440 may include many of the samecomponents as HVAC system 100, as described with reference to FIGS. 1-3.For example, HVAC subsystem 440 may include a chiller, a boiler, anynumber of air handling units, economizers, field controllers,supervisory controllers, actuators, temperature sensors, and otherdevices for controlling the temperature, humidity, airflow, or othervariable conditions within building 10. Lighting subsystem 442 mayinclude any number of light fixtures, ballasts, lighting sensors,dimmers, or other devices configured to controllably adjust the amountof light provided to a building space. Security subsystem 438 mayinclude occupancy sensors, video surveillance cameras, digital videorecorders, video processing servers, intrusion detection devices, accesscontrol devices and servers, or other security-related devices.

Still referring to FIG. 4, BMS controller 366 is shown to include acommunications interface 407 and a BMS interface 409. Interface 407 mayfacilitate communications between BMS controller 366 and externalapplications (e.g., monitoring and reporting applications 422,enterprise control applications 426, remote systems and applications444, applications residing on client devices 448, etc.) for allowinguser control, monitoring, and adjustment to BMS controller 366 and/orsubsystems 428. Interface 407 may also facilitate communications betweenBMS controller 366 and client devices 448. BMS interface 409 mayfacilitate communications between BMS controller 366 and buildingsubsystems 428 (e.g., HVAC, lighting security, lifts, powerdistribution, business, etc.).

Interfaces 407, 409 can be or include wired or wireless communicationsinterfaces (e.g., jacks, antennas, transmitters, receivers,transceivers, wire terminals, etc.) for conducting data communicationswith building subsystems 428 or other external systems or devices. Invarious embodiments, communications via interfaces 407, 409 may bedirect (e.g., local wired or wireless communications) or via acommunications network 446 (e.g., a WAN, the Internet, a cellularnetwork, etc.). For example, interfaces 407, 409 can include an Ethernetcard and port for sending and receiving data via an Ethernet-Basedcommunications link or network. In another example, interfaces 407, 409can include a WiFi transceiver for communicating via a wirelesscommunications network. In another example, one or both of interfaces407, 409 may include cellular or mobile phone communicationstransceivers. In one embodiment, communications interface 407 is a powerline communications interface and BMS interface 409 is an Ethernetinterface. In other embodiments, both communications interface 407 andBMS interface 409 are Ethernet interfaces or are the same Ethernetinterface.

Still referring to FIG. 4, BMS controller 366 is shown to include aprocessing circuit 404 including a processor 406 and memory 408.Processing circuit 404 may be communicably connected to BMS interface409 and/or communications interface 407 such that processing circuit 404and the various components thereof can send and receive data viainterfaces 407, 409. Processor 406 can be implemented as a generalpurpose processor, an application specific integrated circuit (ASIC),one or more field programmable gate arrays (FPGAs), a group ofprocessing components, or other suitable electronic processingcomponents.

Memory 408 (e.g., memory, memory unit, storage device, etc.) may includeone or more devices (e.g., RAM, ROM, Flash memory, hard disk storage,etc.) for storing data and/or computer code for completing orfacilitating the various processes, layers and modules described in thepresent application. Memory 408 may be or include volatile memory ornon-volatile memory. Memory 408 may include database components, objectcode components, script components, or any other type of informationstructure for supporting the various activities and informationstructures described in the present application. According to anexemplary embodiment, memory 408 is communicably connected to processor406 via processing circuit 404 and includes computer code for executing(e.g., by processing circuit 404 and/or processor 406) one or moreprocesses described herein.

In some embodiments, BMS controller 366 is implemented within a singlecomputer (e.g., one server, one housing, etc.). In various otherembodiments BMS controller 366 may be distributed across multipleservers or computers (e.g., that can exist in distributed locations).Further, while FIG. 4 shows applications 422 and 426 as existing outsideof BMS controller 366, in some embodiments, applications 422 and 426 maybe hosted within BMS controller 366 (e.g., within memory 408).

Still referring to FIG. 4, memory 408 is shown to include an enterpriseintegration layer 410, an automated measurement and validation (AM&V)layer 412, a demand response (DR) layer 414, a fault detection anddiagnostics (FDD) layer 416, an integrated control layer 418, and abuilding subsystem integration later 420. Layers 410-420 may beconfigured to receive inputs from building subsystems 428 and other datasources, determine optimal control actions for building subsystems 428Based on the inputs, generate control signals Based on the optimalcontrol actions, and provide the generated control signals to buildingsubsystems 428. The following paragraphs describe some of the generalfunctions performed by each of layers 410-420 in BMS 400.

Enterprise integration layer 410 may be configured to serve clients orlocal applications with information and services to support a variety ofenterprise-level applications. For example, enterprise controlapplications 426 may be configured to provide subsystem-spanning controlto a graphical user interface (GUI) or to any number of enterprise-levelbusiness applications (e.g., accounting systems, user identificationsystems, etc.). Enterprise control applications 426 may also oralternatively be configured to provide configuration GUIs forconfiguring BMS controller 366. In yet other embodiments, enterprisecontrol applications 426 can work with layers 410-420 to optimizebuilding performance (e.g., efficiency, energy use, comfort, or safety)Based on inputs received at interface 407 and/or BMS interface 409.

Building subsystem integration layer 420 may be configured to managecommunications between BMS controller 366 and building subsystems 428.For example, building subsystem integration layer 420 may receive sensordata and input signals from building subsystems 428 and provide outputdata and control signals to building subsystems 428. Building subsystemintegration layer 420 may also be configured to manage communicationsbetween building subsystems 428. Building subsystem integration layer420 translate communications (e.g., sensor data, input signals, outputsignals, etc.) across a plurality of multi-vendor/multi-protocolsystems.

Demand response layer 414 may be configured to optimize resource usage(e.g., electricity use, natural gas use, water use, etc.) and/or themonetary cost of such resource usage in response to satisfy the demandof building 10. The optimization may be Based on time-of-use prices,curtailment signals, energy availability, or other data received fromutility providers, distributed energy generation systems 424, fromenergy storage 427 (e.g., hot TES 242, cold TES 244, etc.), or fromother sources. Demand response layer 414 may receive inputs from otherlayers of BMS controller 366 (e.g., building subsystem integration layer420, integrated control layer 418, etc.). The inputs received from otherlayers may include environmental or sensor inputs such as temperature,carbon dioxide levels, relative humidity levels, air quality sensoroutputs, occupancy sensor outputs, room schedules, and the like. Theinputs may also include inputs such as electrical use (e.g., expressedin kWh), thermal load measurements, pricing information, projectedpricing, smoothed pricing, curtailment signals from utilities, and thelike.

According to an exemplary embodiment, demand response layer 414 includescontrol logic for responding to the data and signals it receives. Theseresponses can include communicating with the control algorithms inintegrated control layer 418, changing control strategies, changingsetpoints, or activating/deactivating building equipment or subsystemsin a controlled manner. Demand response layer 414 may also includecontrol logic configured to determine when to utilize stored energy. Forexample, demand response layer 414 may determine to begin using energyfrom energy storage 427 just prior to the beginning of a peak use hour.

In some embodiments, demand response layer 414 includes a control moduleconfigured to actively initiate control actions (e.g., automaticallychanging setpoints) which minimize energy costs Based on one or moreinputs representative of or Based on demand (e.g., price, a curtailmentsignal, a demand level, etc.). In some embodiments, demand responselayer 414 uses equipment models to determine an optimal set of controlactions. The equipment models may include, for example, thermodynamicmodels describing the inputs, outputs, and/or functions performed byvarious sets of building equipment. Equipment models may representcollections of building equipment (e.g., subplants, chiller arrays,etc.) or individual devices (e.g., individual chillers, heaters, pumps,etc.).

Demand response layer 414 may further include or draw upon one or moredemand response policy definitions (e.g., databases, XML files, etc.).The policy definitions may be edited or adjusted by a user (e.g., via agraphical user interface) so that the control actions initiated inresponse to demand inputs may be tailored for the user's application,desired comfort level, particular building equipment, or Based on otherconcerns. For example, the demand response policy definitions canspecify which equipment may be turned on or off in response toparticular demand inputs, how long a system or piece of equipment shouldbe turned off, what setpoints can be changed, what the allowable setpoint adjustment range is, how long to hold a high demand setpointbefore returning to a normally scheduled setpoint, how close to approachcapacity limits, which equipment modes to utilize, the energy transferrates (e.g., the maximum rate, an alarm rate, other rate boundaryinformation, etc.) into and out of energy storage devices (e.g., thermalstorage tanks, battery banks, etc.), and when to dispatch on-sitegeneration of energy (e.g., via fuel cells, a motor generator set,etc.).

Integrated control layer 418 may be configured to use the data input oroutput of building subsystem integration layer 420 and/or demandresponse later 414 to make control decisions. Due to the subsystemintegration provided by building subsystem integration layer 420,integrated control layer 418 can integrate control activities of thesubsystems 428 such that the subsystems 428 behave as a singleintegrated super-system. In an exemplary embodiment, integrated controllayer 418 includes control logic that uses inputs and outputs from aplurality of building subsystems to provide greater comfort and energysavings relative to the comfort and energy savings that separatesubsystems could provide alone. For example, integrated control layer418 may be configured to use an input from a first subsystem to make anenergy-saving control decision for a second subsystem. Results of thesedecisions can be communicated back to building subsystem integrationlayer 420.

Integrated control layer 418 is shown to be logically below demandresponse layer 414. Integrated control layer 418 may be configured toenhance the effectiveness of demand response layer 414 by enablingbuilding subsystems 428 and their respective control loops to becontrolled in coordination with demand response layer 414. Thisconfiguration may advantageously reduce disruptive demand responsebehavior relative to conventional systems. For example, integratedcontrol layer 418 may be configured to assure that a demandresponse-driven upward adjustment to the setpoint for chilled watertemperature (or another component that directly or indirectly affectstemperature) does not result in an increase in fan energy (or otherenergy used to cool a space) that would result in greater total buildingenergy use than was saved at the chiller.

Integrated control layer 418 may be configured to provide feedback todemand response layer 414 so that demand response layer 414 checks thatconstraints (e.g., temperature, lighting levels, etc.) are properlymaintained even while demanded load shedding is in progress. Theconstraints may also include setpoint or sensed boundaries relating tosafety, equipment operating limits and performance, comfort, fire codes,electrical codes, energy codes, and the like. Integrated control layer418 is also logically below fault detection and diagnostics layer 416and automated measurement and validation layer 412. Integrated controllayer 418 may be configured to provide calculated inputs (e.g.,aggregations) to these higher levels Based on outputs from more than onebuilding subsystem.

Automated measurement and validation (AM&V) layer 412 may be configuredto verify that control strategies commanded by integrated control layer418 or demand response layer 414 are working properly (e.g., using dataaggregated by AM&V layer 412, integrated control layer 418, buildingsubsystem integration layer 420, FDD layer 416, or otherwise). Thecalculations made by AM&V layer 412 may be based on building systemenergy models and/or equipment models for individual BMS devices orsubsystems. For example, AM&V layer 412 may compare a model-predictedoutput with an actual output from building subsystems 428 to determinean accuracy of the model.

Fault detection and diagnostics (FDD) layer 416 may be configured toprovide on-going fault detection for building subsystems 428, buildingsubsystem devices (i.e., building equipment), and control algorithmsused by demand response layer 414 and integrated control layer 418. FDDlayer 416 may receive data inputs from integrated control layer 418,directly from one or more building subsystems or devices, or fromanother data source. FDD layer 416 may automatically diagnose andrespond to detected faults. The responses to detected or diagnosedfaults may include providing an alert message to a user, a maintenancescheduling system, or a control algorithm configured to attempt torepair the fault or to work-around the fault.

FDD layer 416 may be configured to output a specific identification ofthe faulty component or cause of the fault (e.g., loose damper linkage)using detailed subsystem inputs available at building subsystemintegration layer 420. In other exemplary embodiments, FDD layer 416 isconfigured to provide “fault” events to integrated control layer 418which executes control strategies and policies in response to thereceived fault events. According to an exemplary embodiment, FDD layer416 (or a policy executed by an integrated control engine or businessrules engine) may shut-down systems or direct control activities aroundfaulty devices or systems to reduce energy waste, extend equipment life,or assure proper control response.

FDD layer 416 may be configured to store or access a variety ofdifferent system data stores (or data points for live data). FDD layer416 may use some content of the data stores to identify faults at theequipment level (e.g., specific chiller, specific AHU, specific terminalunit, etc.) and other content to identify faults at component orsubsystem levels. For example, building subsystems 428 may generatetemporal (i.e., time-series) data indicating the performance of BMS 400and the various components thereof. The data generated by buildingsubsystems 428 may include measured or calculated values that exhibitstatistical characteristics and provide information about how thecorresponding system or process (e.g., a temperature control process, aflow control process, etc.) is performing in terms of error from itssetpoint. These processes can be examined by FDD layer 416 to exposewhen the system begins to degrade in performance and alert a user torepair the fault before it becomes more severe.

Referring now to FIG. 5, a block diagram of another building managementsystem (BMS) 500 is shown, according to some embodiments. BMS 500 can beused to monitor and control the devices of HVAC system 100, watersidesystem 200, airside system 300, building subsystems 428, as well asother types of BMS devices (e.g., lighting equipment, securityequipment, etc.) and/or HVAC equipment.

BMS 500 provides a system architecture that facilitates automaticequipment discovery and equipment model distribution. Equipmentdiscovery can occur on multiple levels of BMS 500 across multipledifferent communications busses (e.g., a system bus 554, zone buses556-560 and 564, sensor/actuator bus 566, etc.) and across multipledifferent communications protocols. In some embodiments, equipmentdiscovery is accomplished using active node tables, which provide statusinformation for devices connected to each communications bus. Forexample, each communications bus can be monitored for new devices bymonitoring the corresponding active node table for new nodes. When a newdevice is detected, BMS 500 can begin interacting with the new device(e.g., sending control signals, using data from the device) without userinteraction.

Some devices in BMS 500 present themselves to the network usingequipment models. An equipment model defines equipment objectattributes, view definitions, schedules, trends, and the associatedBACnet value objects (e.g., analog value, binary value, multistatevalue, etc.) that are used for integration with other systems. Somedevices in BMS 500 store their own equipment models. Other devices inBMS 500 have equipment models stored externally (e.g., within otherdevices). For example, a zone coordinator 508 can store the equipmentmodel for a bypass damper 528. In some embodiments, zone coordinator 508automatically creates the equipment model for bypass damper 528 or otherdevices on zone bus 558. Other zone coordinators can also createequipment models for devices connected to their zone busses. Theequipment model for a device can be created automatically based on thetypes of data points exposed by the device on the zone bus, device type,and/or other device attributes. Several examples of automatic equipmentdiscovery and equipment model distribution are discussed in greaterdetail below.

Still referring to FIG. 5, BMS 500 is shown to include a system manager502; several zone coordinators 506, 508, 510 and 518; and several zonecontrollers 524, 530, 532, 536, 548, and 550. System manager 502 canmonitor data points in BMS 500 and report monitored variables to variousmonitoring and/or control applications. System manager 502 cancommunicate with client devices 504 (e.g., user devices, desktopcomputers, laptop computers, mobile devices, etc.) via a datacommunications link 574 (e.g., BACnet IP, Ethernet, wired or wirelesscommunications, etc.). System manager 502 can provide a user interfaceto client devices 504 via data communications link 574. The userinterface may allow users to monitor and/or control BMS 500 via clientdevices 504.

In some embodiments, system manager 502 is connected with zonecoordinators 506-510 and 518 via a system bus 554. System manager 502can be configured to communicate with zone coordinators 506-510 and 518via system bus 554 using a master-slave token passing (MSTP) protocol orany other communications protocol. System bus 554 can also connectsystem manager 502 with other devices such as a constant volume (CV)rooftop unit (RTU) 512, an input/output module (IOM) 514, a thermostatcontroller 516 (e.g., a TEC5000 series thermostat controller), and anetwork automation engine (NAE) or third-party controller 520. RTU 512can be configured to communicate directly with system manager 502 andcan be connected directly to system bus 554. Other RTUs can communicatewith system manager 502 via an intermediate device. For example, a wiredinput 562 can connect a third-party RTU 542 to thermostat controller516, which connects to system bus 554.

System manager 502 can provide a user interface for any devicecontaining an equipment model. Devices such as zone coordinators 506-510and 518 and thermostat controller 516 can provide their equipment modelsto system manager 502 via system bus 554. In some embodiments, systemmanager 502 automatically creates equipment models for connected devicesthat do not contain an equipment model (e.g., IOM 514, third partycontroller 520, etc.). For example, system manager 502 can create anequipment model for any device that responds to a device tree request.The equipment models created by system manager 502 can be stored withinsystem manager 502. System manager 502 can then provide a user interfacefor devices that do not contain their own equipment models using theequipment models created by system manager 502. In some embodiments,system manager 502 stores a view definition for each type of equipmentconnected via system bus 554 and uses the stored view definition togenerate a user interface for the equipment.

Each zone coordinator 506-510 and 518 can be connected with one or moreof zone controllers 524, 530-532, 536, and 548-550 via zone buses 556,558, 560, and 564. Zone coordinators 506-510 and 518 can communicatewith zone controllers 524, 530-532, 536, and 548-550 via zone busses556-560 and 564 using a MSTP protocol or any other communicationsprotocol. Zone busses 556-560 and 564 can also connect zone coordinators506-510 and 518 with other types of devices such as variable air volume(VAV) RTUs 522 and 540, changeover bypass (COBP) RTUs 526 and 552,bypass dampers 528 and 546, and PEAK controllers 534 and 544.

Zone coordinators 506-510 and 518 can be configured to monitor andcommand various zoning systems. In some embodiments, each zonecoordinator 506-510 and 518 monitors and commands a separate zoningsystem and is connected to the zoning system via a separate zone bus.For example, zone coordinator 506 can be connected to VAV RTU 522 andzone controller 524 via zone bus 556. Zone coordinator 508 can beconnected to COBP RTU 526, bypass damper 528, COBP zone controller 530,and VAV zone controller 532 via zone bus 558. Zone coordinator 510 canbe connected to PEAK controller 534 and VAV zone controller 536 via zonebus 560. Zone coordinator 518 can be connected to PEAK controller 544,bypass damper 546, COBP zone controller 548, and VAV zone controller 550via zone bus 564.

A single model of zone coordinator 506-510 and 518 can be configured tohandle multiple different types of zoning systems (e.g., a VAV zoningsystem, a COBP zoning system, etc.). Each zoning system can include aRTU, one or more zone controllers, and/or a bypass damper. For example,zone coordinators 506 and 510 are shown as Verasys VAV engines (VVEs)connected to VAV RTUs 522 and 540, respectively. Zone coordinator 506 isconnected directly to VAV RTU 522 via zone bus 556, whereas zonecoordinator 510 is connected to a third-party VAV RTU 540 via a wiredinput 568 provided to PEAK controller 534. Zone coordinators 508 and 518are shown as Verasys COBP engines (VCEs) connected to COBP RTUs 526 and552, respectively. Zone coordinator 508 is connected directly to COBPRTU 526 via zone bus 558, whereas zone coordinator 518 is connected to athird-party COBP RTU 552 via a wired input 570 provided to PEAKcontroller 544.

Zone controllers 524, 530-532, 536, and 548-550 can communicate withindividual BMS devices (e.g., sensors, actuators, etc.) viasensor/actuator (SA) busses. For example, VAV zone controller 536 isshown connected to networked sensors 538 via SA bus 566. Zone controller536 can communicate with networked sensors 538 using a MSTP protocol orany other communications protocol. Although only one SA bus 566 is shownin FIG. 5, it should be understood that each zone controller 524,530-532, 536, and 548-550 can be connected to a different SA bus. EachSA bus can connect a zone controller with various sensors (e.g.,temperature sensors, humidity sensors, pressure sensors, light sensors,occupancy sensors, etc.), actuators (e.g., damper actuators, valveactuators, etc.) and/or other types of controllable equipment (e.g.,chillers, heaters, fans, pumps, etc.).

Each zone controller 524, 530-532, 536, and 548-550 can be configured tomonitor and control a different building zone. Zone controllers 524,530-532, 536, and 548-550 can use the inputs and outputs provided viatheir SA busses to monitor and control various building zones. Forexample, a zone controller 536 can use a temperature input received fromnetworked sensors 538 via SA bus 566 (e.g., a measured temperature of abuilding zone) as feedback in a temperature control algorithm. Zonecontrollers 524, 530-532, 536, and 548-550 can use various types ofcontrol algorithms (e.g., state-based algorithms, extremum seekingcontrol (ESC) algorithms, proportional-integral (PI) control algorithms,proportional-integral-derivative (PID) control algorithms, modelpredictive control (MPC) algorithms, feedback control algorithms, etc.)to control a variable state or condition (e.g., temperature, humidity,airflow, lighting, etc.) in or around building 10.

BMS with Semantic Modeling

Referring now to FIG. 6, a block diagram of a semantic modeling system600 is shown, according to some embodiments. System 600 is generallyconfigured to generate a semantic site model for a BMS based on a BMSontology data model. The BMS ontology data model generally describesobjects in a BMS (e.g., equipment, spaces, points) and objectrelationships in a semantic or natural manner (e.g., using a semanticdescription schema). A BMS ontology data model can be applied to a BMSthrough the mapping or classifying of building metadata to the BMSontology data model. In this regard, the BMS ontology data model may“standardize” a BMS (e.g., the BMS configuration data) according to theBMS ontology data model, to provide for improved monitoring, reporting,and commanding of the BMS with minimal user interaction. Additionally, astandardized BMS may be more user friendly than other systems, bydefining BMS object relationships in an easy-to-understand format.

System 600 is shown to include a processing circuit 602, which furtherincludes a processor 604 and memory 610. It will be appreciated thatthese components can be implemented using a variety of different typesand quantities of processors and memory. Processor 604 can beimplemented as a general purpose processor, an application specificintegrated circuit (ASIC), one or more field programmable gate arrays(FPGAs), a group of processing components, or other suitable electronicprocessing components.

Memory 610 (e.g., memory, memory unit, storage device, etc.) can includeone or more devices (e.g., RAM, ROM, Flash memory, hard disk storage,etc.) for storing data and/or computer code for completing orfacilitating the processes, layers and modules described in the presentapplication. Memory 610 can be or include volatile memory ornon-volatile memory. Memory 610 can include database components, objectcode components, script components, or any other type of informationstructure for supporting the activities and information structuresdescribed in the present application. According to an exampleembodiment, memory 610 is communicably connected to processor 604 viaprocessing circuit 602 and includes computer code for executing (e.g.,by processing circuit 602 and/or processor 604) one or more processesdescribed herein.

In some embodiments, processing circuit 602 is implemented within asingle computer (e.g., one server, one housing, etc.). In otherembodiments processing circuit 602 can be distributed across multipleservers or computers (e.g., that can exist in distributed locations). Insome embodiments, system 600 and/or processing circuit 602 is embodiedin the BMS 400 as described above, and accordingly, processing circuit602, processor 604, and/or memory 610 may be similar to or the same asprocessing circuit 404, processor 406 and/or memory 408 as describedabove. Additionally, in such embodiments, a portion of the components ofmemory 610, described below, may be embodied in the BMS 400.

In some embodiments, system 600 is a stand-alone device or component notembodied in the BMS 400, and therefore includes its own dedicatedprocessing circuit 602, processor 604, and/or memory 610. In otherembodiments, system 600 is embodied as a portion of the BMS 400, adifferently arranged BMS, or a building automation system (BAS), andaccordingly may share a processing circuit, processor, and/or memorywith any of these other BMSs or BASs. In yet other embodiments, aportion of system 600 (e.g., certain components of memory 610, describedbelow) may be implemented via a system configuration tool, as describedbelow with respect to FIG. 7B. A system configuration tool may beimplement prior to configuring a particular BMS or a particular buildingsite (e.g., prior to construction of the building, prior to operatingbuilding equipment, prior to activating or implementing a BMS, etc.),for example. Accordingly certain components of memory 610 may beimplemented prior to operating a BMS (e.g., BMS 400).

Memory 610 is shown to include an object definition generator 612.Object definition generator 612 is generally configured to obtainunmapped object definitions (e.g., from an object database 620), and toapply user preferences and an ontology data model to the unmapped objectdefinitions. An unmapped object definition is generally an abstractionof an object associated with a BMS. For example, an unmapped objectdefinition may include generic or unmodified parameters, identifiers,labels, etc., associated with a BMS object (e.g., equipment, a space, apoint). In general, an unmapped object definition includes at least aname and an identifier. In some embodiments, the unmapped objectdefinitions may be structured according to a first data schema (e.g.,BACnet). Accordingly, the name and/or identifier for an unmapped objectdefinition may not be in a semantic format. For example, the unmappedobject definition may include parameters and/or identifiers in a machinelanguage, or in a schema that is not configured to be human-readable.

In some embodiments, an unmapped object definition also includes a setof point definitions typically associated with the BMS object reprintedby the unmapped object definition. For example, an unmapped objectdefinition for a chiller type BMS object may include a plurality ofpoint definitions corresponding to points typically associated with achiller (e.g., outlet water temperature, pump speed, pressure, etc.).Object database 620 may include a library of previously defined BMSobject definitions associated with a variety of objects commonly foundin a BMS. For example, object database 620 may include a library ofunmapped object definitions corresponding to any of the buildingequipment described above (e.g., building subsystems 428), and to any ofa plurality of spaces or points in a building site.

Object definition generator 612 may obtain an ontology data model 622 inorder to generate mapped object definitions from the unmapped objectdefinitions. Ontology data model 622 is generally a common data modelthat defines BMS objects according to a semantic description schema.Ontology data model 622 may include standardized names, types,parameters, etc., for a variety of objects found in a BMS (e.g., spaces,equipment, and points). Ontology data model 622 can include a taglibrary comprising a set of tags that may be applied to unmapped objectdefinitions. The tags may include semantic descriptions corresponding toeach of the parameters of an object definition. For example, the tagsmay include semantic (i.e., plain language) labels, short names, searchcriteria, etc., that may be applied to an unmapped object definition.Ontology data model 622 may also define standardized parameters for eachtype of tag stored in the tag library. Further, ontology data model 622may define relationships between tags. Accordingly, applying ontologydata model 622 to unmapped object definitions may not only translate theunmapped object definitions into a common and/or semantic descriptionschema, but ontology data model 622 may also define relationshipsbetween object definitions semantically. For example, ontology datamodel 622 may indicate that an object definition for a chiller “serves”an object definition for an air handler. In some embodiments, ontologydata model 622 is retrieved from a semantic model database, as describedin any of U.S. patent application Ser. No. 16/379,646, U.S. patentapplication Ser. No. 16/379,652, U.S. patent application Ser. No.16/379,661, or U.S. patent application Ser. No. 16/379,666, all of whichare incorporated herein by reference in their entireties.

Object definition generator 612 may be configured to generate mappedobject definitions from the unmapped object definitions by applying userpreferences and/or the ontology data model 622 to one or more unmappedobject definitions. To achieve this, object definition generator 612 mayanalyze the various unmapped object definitions to identify, for eachunmapped object definition, an object name or other similar identifier.Based on the object name, object definition generator 612 may determinea corresponding tag or tag set from the ontology data model 622, and mayapply or map the tag or tag set to the unmapped object definition. Insome embodiments, this also includes applying any user preferences tothe unmapped object. The user preferences may include user-defineidentifiers or labels for certain object definitions, and in some casescan include a model class for certain object definitions.

Memory 610 is also shown to include a classification engine 614,configured to identify BMS objects from BMS configuration data and toclassify the BMS objects based on the mapped object definitionsgenerated by object definition generator 612. More specifically,classification engine 614 may classify BMS objects identified from theBMS configuration data by identifying one or more BMS objects thatsatisfy (i.e., match) a mapped object definition in the semantic model,and by classifying or mapping the one or more identified BMS objects tothe mapped object definition. In this regard, any parameters of themapped object definition (e.g., associated point definitions) may alsobe associated with the one or more identified BMS objects. For example,the one or more BMS object may be classified according to a model classassigned to the mapped object definition and/or the point definitionsassociated with the mapped object definition. A semantic site model maybe generated for a BMS or a building site based on this classificationof the BMS objects associated with the BMS or building site according tothe mapped object definitions and assigned model classes. In someembodiments, the semantic site model is generated in a similar manner tothe semantic models described in any of U.S. patent application Ser. No.16/379,646, U.S. patent application Ser. No. 16/379,652, U.S. patentapplication Ser. No. 16/379,661, or U.S. patent application Ser. No.16/379,666, mentioned above.

In some embodiments, classification engine 614 is also configured toobtain configuration data for a BMS by scanning, mining, or otherwiseanalyzing a BMS (e.g., BMS 400) to detect and identify BMS objects suchas equipment, spaces (e.g., floors, rooms, levels, etc.), and/or pointsassociated with the BMS. For example, classification engine 614 may minea BMS to identify equipment (e.g., HVAC equipment) and to identifyspaces served by the equipment. In this regard, classification engine614 may be configured to generate and/or update the BMS configurationbased on the identification of BMS objects.

Memory 610 is also shown to include a fault detection and diagnostics(FDD) engine 616. FDD engine 616 is configured to determine one or morefault detection and/or diagnostic rules for a BMS, and to monitor theBMS to detect faults or perform diagnostic procedures. In someembodiments, FDD engine 616 is structured in a similar manner to thefault detection system described in U.S. Pat. No. 8,788,097,incorporated herein by reference in its entirety. FDD engine 616 mayobtain fault detection or diagnostic rules from a user input, forexample, or may obtain the rule by any other method (e.g., from adatabase).

FDD engine 616 may also be configured to monitor operating datacorresponding to equipment, spaces, and/or points of a BMS. Said datamay include, for example, current operating states or parameters, sensoror meter readings, etc. FDD engine 616 can compare the received datawith the fault detection and diagnostic rules to detect a faultcondition. A fault condition may indicate that a particular BMS objectmeets one or more fault criteria, which may in turn indicate an issuewith one or more BMS objects (e.g., equipment). As an example, a faultdetection and diagnostic rule may define a desired temperature range fora space in a building site. If FDD engine 616 determines that the airtemperature within the space exceeds a threshold corresponding to thedesire temperature range (e.g., based on sensor data), FDD engine 616may indicate a fault.

In some embodiments, FDD engine 616 may utilize a previously generatedsemantic site model to identify BMS objects associated with a faultdetection rule. Specifically, for each application or implementation ofa fault detection rule, FDD engine 616 can determine one or more BMSobject needed to evaluate the rule using the semantic site model. TheBMS objects may be identified based on the fault criteria for each faultdetection rule. For example, the fault criteria may require a particulartype of sensor measurement, a particular value, etc. When the faultdetection rule is applied to a particular space, equipment, or point ofa BMS or a building, the semantic site model may be used to identify theparticular BMS objects that are referenced to determine the faultcriteria.

In some embodiments, FDD engine 616 may also initiate automatedcorrective actions based on a detected fault condition. In someembodiments, a corrective action may be predetermined based on the typeof fault condition, the fault detection rule, the BMS objects associatedwith the fault condition, etc. The corrective action may include, forexample, controlling building equipment associated with the BMS objectsin order to affect one or more parameters associated with the BMSobjects. The corrective action can also include generating andtransmitting a notification or a work order based on the detected fault.

A user interface generator 618 is configured to generate graphical userinterfaces relating system 600. For example, user interface generator618 may generate a graphical user interface for the user to enterpreferences for a mapping object definitions, as discussed above withrespect to object definition generator 612. In some embodiments, userinterface generator 618 may provide a user interface to allow the userto define or select a model class for one or more object definitions.User interface generator 618 may also generate interfaces that allow auser to interact with a BMS (e.g., BMS 400), particularly after theBMS's configuration data has been classified according to mapped objectdefinitions, as discussed above. It will be appreciated, however, thatuser interface generator 618 may be generally configured to generate anysort of graphical user interface.

Still referring to FIG. 6, system 600 is shown to include acommunications interface 630. Processing circuit 602 can be communicablyconnected to communications interface 630 such that processing circuit602 and the components thereof can send and receive data via thecommunications interface 630. System 600 may exchange data with network446 and/or user device 632 via a communications interface 630, forexample. Communications interface 630 may include a wired and/orwireless interface for connecting system 600 to network 446 and/or auser device 632. For example, communications interface 630 may include awireless network adaptor for wirelessly connecting system 600 to network446. In some embodiments, communications interface 630 also provides aninterface between system 600, and any one or more the buildingsubsystems 428, or other components of the BMS 400 or BMS 500 describedabove. In this regard, communications interface 630 can include a BACnetinterface in addition to other types of communications interfaces (e.g.,Modbus, LonWorks, DeviceNet, XML, etc.).

User device 632 may be any electronic device that allows a user tointeract with system 600 through a user interface. Examples of userdevices include, but are not limited to, mobile phones, electronictablets, laptops, desktop computers, workstations, and other types ofelectronic devices. User device 632 may be similar to client device 368and/or client devices 504, as described above. User device 632 maydisplay graphical user interfaces or other data on a display, therebyenabling a user to easily view data and interact with system 600. Forexample, user device 632 may present any of the user interfacesgenerated by user interface generator 618.

Referring now to FIG. 7A, a block diagram of a semantic modelingarchitecture 700 is shown, according to some embodiments. Architecture700 may be implemented by system 600, for example, and accordingly mayillustrate the generation of a semantic site model by system 600.Architecture 700 is shown to include unmapped object definitions 702 anduser preferences 704. Unmapped object definitions 702 can include one ormore objects, data sets, files, etc., corresponding to one or more BMSobject definitions, as described above with respect to FIG. 6.Similarly, user preferences 704 can include one or more individualsettings, files, data sets, etc., that define user preferences. Ingeneral, user preferences 704 may include at least an indication of amodel class to assign to each of one or more BMS object definitions. Insome embodiments, user preferences 704 also include user selections ofother object definition parameters, including BMS object labels,configuration settings, point definition labels, point definition shortnames (i.e., identifiers), and/or point definition search criteria.

Unmapped object definitions 702 and user preferences 704 may be obtainedby, or fed into, object definition generator 612, along with ontologydata model 622. As described above, object definition generator 612 mayapply ontology data model 622 and/or user preferences 704 to unmappedobject definitions 702. For example, object definition generator 612 maymap the unmapped object definitions 702 to corresponding objectdefinitions in ontology data model 622, and may subsequently orconcurrently apply user preferences 704 to add, remove, or modify one ormore parameters of each object definition. In other words, unmappedobject definitions 702, user preferences 704, and ontology data model622 may be combined or married by object definition generator 612 togenerate mapped object definitions 706. Mapped object definitions 706may then be stored in object database 620.

As a non-limiting example, an unmapped object definition (e.g., one ofunmapped object definitions 702) for a particular BMS objectrepresenting an AHU may be obtained by object definition generator 612,along with ontology data model 622. Ontology data model 622 may includea variety of standardized information for AHU objects, such as AHUparameters (e.g., temperatures, fan speed, capacity, etc.), along with aplurality of point definitions associated with an AHU object. Each pointdefinition may represent a particular point, sensor, device, etc.,associated with a physical AHU. For example, the AHU object may includepoint definitions for fan status, fan speed, output air temperature,etc. Additionally, ontology data model 622 may define a plurality ofmodel classes that can be assigned to BMS objects, and may also indicatemodel class relationships. User preferences 704 may include at least auser selection of a model class to apply to AHU objects. Objectdefinition generator 612 can map the unmapped AHU object to the ontologydata model 622 and can assign user preferences 704 to AHU object.

Mapped object definitions 706 can be retrieved or transmitted fromobject database 620 to classification engine 614. Classification engine614 may also obtain BMS configuration data 708 for a particular BMSand/or a particular building site, in order to apply mapped objectdefinitions 706 to BMS configuration data 708. As described above withrespect to FIG. 6, classification engine 614 may classify BMSconfiguration data 708, which can include objects corresponding toequipment, spaces, and/or points in a BMS (e.g., BMS 400), based onmapped object definitions 706. In other words, classification engine 614can classify each BMS object of BMS configuration data 708 to acorresponding mapped object definition (e.g., one of mapped objectdefinitions 706). Accordingly, each BMS object is also classifiedaccording to a model class assigned to a corresponding one of the mappedobject definitions 706. The output of classification engine 614 is shownas a semantic site model 710. As described above, semantic site model710 may be a model of a complete building site or a complete BMS thatdefines each BMS object associated with the site or BMS (e.g., eachspace, device, and/or point) according to mapped object definitions 706,and thereby according to ontology data model 622 and user preferences704.

To continue the example above, the mapped object definition for the AHUcan be retrieved from object database 620 by classification engine 614.Subsequently, configuration data for a first BMS that includes BMSobjects for each of the equipment, spaces, and points within the firstBMS may be obtain. The configuration data may be analyzed byclassification engine 614 to identify any BMS objects that correspond toan AHU. The identified BMS objects may then be classified as, or mappedto, the mapped object definition for the AHU.

Referring now to FIG. 7B, an implementation of architecture 700 isshown, according to some embodiments. In particular, FIG. 7B showsvarious components of architecture 700 performed by a systemconfiguration tool 720 and a BMS 740. As mentioned above, systemconfiguration tool 720 may be a separate and/or remote system from a BMS(e.g., BMS 400), and/or may be a subsystem implemented within a BMS. Inany case, system configuration tool 720 is generally configured to beimplemented prior to operating a BMS (e.g., prior to construction of abuilding, prior to operating building equipment, etc.), in order toconfigure the BMS for operations. For example, system configuration tool720 may be implemented prior to activating a BMS in order to configureBMS objects. In some embodiments, system configuration tool 720 isimplemented when BMS 740 is offline, or when equipment of BMS 740 isdisconnected.

System configuration tool 720 is show to include a processing circuit722. Processing circuit 722 is shown to further include a processor 724and memory 730. Similarly, BMS 740 is shown to include a processingcircuit 742, further including a processor 744 and 730. It will beappreciated that BMS 740 may be substantially similar to, or the sameas, either BMS 400 or BMS 500 described above. It will also beappreciated that these components can be implemented using a variety ofdifferent types and quantities of processors and memory. Processor 724and/or processor 744 can be implemented as a general purpose processor,an application specific integrated circuit (ASIC), one or more fieldprogrammable gate arrays (FPGAs), a group of processing components, orother suitable electronic processing components.

Memory 730 and/or memory 750 (e.g., memory, memory unit, storage device,etc.) can include one or more devices (e.g., RAM, ROM, Flash memory,hard disk storage, etc.) for storing data and/or computer code forcompleting or facilitating the processes, layers and modules describedin the present application. Memory 730 and/or memory 750 can be orinclude volatile memory or non-volatile memory. Memory 730 and/or memory750 can include database components, object code components, scriptcomponents, or any other type of information structure for supportingthe activities and information structures described in the presentapplication. In some embodiments, memory 730 and/or memory 750 arecommunicably connected to a corresponding one of processor 724 orprocessor 744 via processing circuit 722 or processing circuit 724. Eachof memory 730 and memory 750 can include computer code for executing oneor more processes described herein.

As shown, system configuration tool 720 may be configured to generatemapped object definitions 706 based on unmapped object definitions 702,user preferences 704, and ontology data model 622, as described abovewith respect to FIG. 7A. In this manner, mapped object definitions 706may be generated prior to implementing, activating, or otherwiseoperating a BMS (e.g., BMS 740). For example, mapped object definitions706 may be generated as part of a configuration process for BMS 740.Mapped object definitions 706 may be stored in object database 620 andsubsequently transmitted to BMS 740 to generate semantic site model 710.In some embodiments, BMS 740 may receive mapped object definitions 706as part of a configuration process, such as after implementing,activating, or otherwise operating BMS 740 and/or building equipment.For example, BMS 740 may receive mapped object definitions 706 after BMS740 and any associated equipment is installed in a building, and afterBMS 740 and/or the equipment is turned on or operated.

In some embodiments, BMS configuration data 708 is also generated onceBMS 740 is activate or operated. For example, once BMS 740 is turned onand any associated equipment is connected, BMS 740 can be mined oranalyzed to identify BMS objects corresponding to equipment, spaces,points, etc., as described above. The identified BMS objects and/orobject relationships may be defined in BMS configuration data 708. BMS740 may then classify BMS configuration data 708 according to mappedobject definitions 706 in order to generate semantic site model 710, asdescribed above. Semantic site model 710 may be referenced by a user ofBMS 740 in subsequent operations.

Referring now to FIG. 8, a flowchart of a process 800 for generating asemantic site model is shown, according to some embodiments. Process 800can be implemented by system 600 in order to generate a semantic modelof a building or site served by BMS 400 or BMS 500, for example. Asmentioned above, a semantic site model may beneficially “standardize” aBMS or building site according to a common data model. A standardizedBMS may be easier for a user to understand and interact with, bydescribing BMS objects and object relationships semantically, and asemantic site model may decrease configuration time for new BMSs.Additionally, the semantic site model may classify BMS objects accordingto model classes to group BMS objects and to clearly identify BMS objectrelationships. It will be appreciated that certain steps of the process800 may be optional and, in some embodiments, the process 800 may beimplemented using less than all of the steps. In some embodiments,certain steps of process 800 may be performed by system configurationtool 720 and other steps may be performed by BMS 740, as described abovewith respect to FIG. 7B. For example, steps 802-806 can be performed bysystem configuration tool 720 while step 808-812 can be performed by BMS740.

At step 802, a BMS ontology data model is obtained. As described above,the BMS ontology data model is generally a common data model thatdefines BMS objects according to a semantic description schema. The BMSontology data model may include a tag library for describing a varietyof objects found in a BMS (e.g., spaces, equipment, and points). The BMSontology data model may also include a plurality of BMS model classesthat can be assigned to various BMS objects and/or to various pointdefinitions associated with a BMS object. A BMS model class is generallya semantic identifier that can be applied to a BMS object. For example,a BMS model class may indicate a type of equipment, space, or point.

At step 804, unmapped BMS object definitions are obtained. The unmappedBMS object definitions may be obtained from a database, for example. Theunmapped BMS object definitions can include equipment definitions for avariety of different types of building equipment and/or pointdefinitions for a variety of points associated with building equipment.An unmapped BMS object definition may be an abstracted representation ofa particular type of building equipment, for example, and the unmappedBMS object definition may include a plurality of point definitionstypically associated with the particular type of building equipment. Forexample, and as described in greater detail with respect to FIGS.10A-10C, an unmapped BMS object definition for a VAV (e.g., VAV units116) may include point definitions for zone air temperature, zone airsetpoint, and supply fan status points. In some embodiments, theunmapped BMS object definitions can also include space definitions for avariety of different spaces within a building site, and can includeadditional point definitions for points associated with the differentspaces.

At step 806, a BMS model class is assigned to each of the unmapped BMSobject definitions. As described above, a model class is generally asemantic identifier that can be applied to a BMS object definition.Model classes can be used to classify or otherwise indicate a type ofequipment, space, or point. For example, the model class may be a textsting or a label that identifies a class for a particular unmappedobject definition, or for an equipment or a point definition associatedwith an unmapped object definition. In some embodiments, the BMS modelclass is automatically assigned to one or more unmapped BMS objectdefinitions based on one or more parameters of the unmapped BMS objectdefinitions. For example, search criteria (e.g., search terms), a shortname, a type, a label, etc., associated with the unmapped BMS objectdefinition may be identified, and a model class may be assigned based onany of the identified parameters.

In other embodiments, a user selection of a model class is received foreach BMS object definition. For example, the user may select a modelclass from a list (e.g., based on the ontology data model) in order toassigned the selected model class to an unmapped BMS object definition.In some embodiments, a user may also defined one or more additional BMSobject identifiers. In such embodiments, a user selection specifying oneor more user-defined identifiers (e.g., short name, label, etc.)associated with a first unmapped BMS object definition may be received.The user selection of a model class and/or user defined identifiers forBMS object definitions is described in greater detail with respect toFIGS. 10A-11B.

In some embodiments, step 806 also includes applying the BMS ontologydata model to the unmapped BMS object definitions. In some suchembodiments, the BMS ontology data model is applied to the unmapped BMSobject definitions concurrently with, or before or after, the modelclasses are assigned. As discussed above, mapped BMS object definitionsare generated based on the assignment of model classes and/or theapplication of the BMS ontology data model. In other words, thepreviously unmapped BMS object definitions may be mapped to the BMSontology data model in order to standardize the BMS object definitions,and the model classes are applied.

At step 808, a BMS is analyzed to identify BMS objects associated with abuilding site. In some embodiments, BMS configuration data can be mined,scanned, or otherwise analyzed to identify BMS object associated with aparticular site. For example, the BMS configuration data is analyzed todetermine the various spaces, points, and/or equipment associated withthe building site and/or controlled by a BMS of the building site. BMSobjects can include equipment entities representing specific instancesof building equipment and point entities representing specific points inthe BMS. BMS objects can also include space entities representingspecific building spaces. In some embodiments, a BMS itself may be minedor analyzed in order to generate the configuration data.

At step 810, a semantic site model is generated by classifying the BMSobjects based on the BMS object definitions and the model classesassigned to each of the BMS object definitions. In other words, the BMSobject identified at step 808 may be classified or mapped tocorresponding BMS object definitions, and thereby may be classified ormapped according to the model classes assigned to each BMS objectdefinition. In some embodiments, BMS objects are classified according toan object identifier associated with each of the BMS object definitions.The object identifier may be a short name, a label, a number, or anothertype of identifier associated with each BMS object definition. Forexample, a first BMS object definition corresponding to a VAV typeobject may include a short name of “SF-S,” which corresponds to a supplyfan status. The BMS objects identified at step 808 may be analyzed todetect any BMS objects that also include an identifier of “SF-S.” Insome cases, search criteria may also be utilized to identify BMSobjects. For example, the search criteria may include additionalidentifiers associated with a supply fan status. The BMS objects mayalso be analyzed to identify any BMS objects that include identifierscorresponding to the search criteria.

At step 812, building equipment is monitored and/or controlled based onthe semantic site model. In some embodiments, the semantic site model isutilized to monitor equipment operations. In some embodiments, a userinterface may be generated to present the semantic site model, or topresent data associated with the semantic site model such as equipmentor site operational data. In some embodiments, controlling the buildingequipment can include adjusting one or more operating parametersassociated with the building equipment. For example, a setpoint may bemodified for a particular building device. In any case, the semanticsite model generated by process 800 may, advantageously, provide a userfriendly method for interacting with a BMS. For example, the semanticsite model defines BMS objects in a natural language that is easy forusers to understand.

Additionally, the classification of BMS objects based on model classesand the relationships between BMS objects defined in the semantic sitemodel can aid in system analytics or querying. Instead of searching fora BMS object by a string of characters or manually tracing equipmentrelationships, for example, a user may query the system (e.g., system600) in a more natural way. For example, the user can ask the systemsimple questions, such as “what are the temperatures of all meetingrooms on the fourth floor?” Using the semantic site model, the systemcould search for BMS objects having a model class of “Zone AirTemperature” and could narrow the search to BMS objects related tospaces on the fourth floor of a building site. In this manner, thesemantic site model may greatly increase user friendliness, and can alsoincrease interoperability with other systems.

Referring now to FIG. 9, a flowchart of a process 900 for faultdetection and diagnostics using a semantic site model is shown,according to some embodiments. Process 900 can be implemented by system600 in order to facilitate fault detection and/or diagnostics for a BMS,for example. Process 900 may utilize a semantic site model to identifyBMS objects associated with fault detection and diagnostic rules. Inthis regard, process 900 does not necessarily require that faultdetection and diagnostics rules reference a particular BMS object.Advantageously, process 900 may allow for generic or non-site specificfault detection and diagnostic rules to be implemented and evaluatedacross a range of building sites or BMSs. It will be appreciated thatcertain steps of the process 900 may be optional and, in someembodiments, the process 900 may be implemented using less than all ofthe steps.

At step 902, at least one fault detection rule is obtained. The faultdetection rule generally includes one or more fault criteria that areevaluated using BMS data (e.g., operating data) to detect faultconditions. Unlike fault detections rules for certain other systems, thefault detection rule obtain at step 902 does not include fault criteriathat reference to a particular BMS object. In other words, the faultcriteria are defined without reference to a particular BMS object. Thisallows the fault detection rule to be applied to any number of differentbuilding sites or BMSs, because the fault criteria do not rely on aparticular BMS object. Additionally, the fault detections rule may bestructured more broadly than other rules that rely on a particularobject, and may be defined in a more natural way.

An example fault detection rule may include fault criteria such as “IFzone temperature is greater than a threshold AND a VAV damper positionis closed” that, if true, may indicate a fault condition. In thisexample, the fault criteria variables of “zone temperature,”“threshold,” and “VAV damper position” can be defined in the faultdetection rule without reference to the particular BMS object or objectsthat need to be analyzed in order to determine whether the faultdetection rule is satisfied. For example, the particular temperaturesensor corresponding to “zone temperature” and/or the particular VAVthat supplies the “zone” or space do not need to be defined in the faultdetection rule.

At step 904, a semantic site model (e.g., generated using process 800)is used to identify the particular BMS objects needed to evaluate thefault criteria. For example, the fault detection rule may be applied toa particular space or equipment of a BMS, and the semantic site modelmay be used to identify BMS object associated with the particular spaceor equipment. As described above, a single fault detection rule mayadvantageously be applied to multiple different building spaces,devices, points, etc. Accordingly, for each implementation orapplication of the fault detection rule, a new set of BMS objects may beidentified to evaluate the fault criteria.

To continue the example above, the fault detection rule including faultcriteria such as “IF zone temperature is greater than a threshold AND aVAV damper position is closed” could be applied to a particular buildingspace (e.g., a room). The semantic site model could be used to identifya specific zone temperature sensor that provides the “zone temperature”for the particular space, a particular threshold value, and a particularVAV or damper that controls airflow to the particular space. In thiscase, the relationships defined by the semantic site model may be usedto identify the zone temperature sensor and/or VAV associated with thespace, and the threshold value may be a parameter associated with a BMSobject representing the particular space.

At step 906, a fault condition is detected by evaluating the faultcriteria using data related to the particular BMS objects. Said data mayinclude, for example, operational data or other data received from BMSobjects represented in the semantic data model. For example, the datacould include values from sensors or equipment within a buildingrepresented by the semantic site model. The received BMS object data maybe compared to a value or a threshold for each fault criteria todetermine if the fault criteria are “true” or “false.” Depending on theparticular fault detection rule, a fault condition may be detected ifone or more of the fault criteria are “true.” In some cases, multiplefault criteria or even all of the fault criteria may need to be “true”in order for a fault condition to be detected.

In the example above, the fault criteria may be evaluated by determininga reading (i.e., value) from the zone temperature sensor associated withthe particular space, as identified using the semantic data model, andcomparing the temperature sensor value to the threshold value obtainedfrom the BMS object representing the particular space. Similarly, avalue may be obtained from a sensor indicating a position of the damperfor a VAV supplying the particular space, and the damper position may beanalyzed to determine with the VAV damper position is “closed,” andtherefore matches the fault criteria.

At step 908, an automated corrective action is initiated in response todetecting a fault condition. The automated corrective action may includeone or more individual corrective actions. For example, the automatedcorrective action can include controlling building equipment. In someembodiments, equipment can be controlled by adjusting an operatingparameter of the equipment, turning the equipment off, taking theequipment office, activating additional equipment, etc. Generally, theequipment are controlled to correct the detected fault condition. Inother words, the equipment can be controlled to affect one or moreparameters associated with the fault criteria. For example, if a zonetemperature is above a threshold value, HVAC equipment may be operatedto reduce the temperature of a space corresponding to the zonetemperature.

In some embodiments, the automated corrective action can includegenerating a work order and/or scheduling a maintenance activity forfaulty equipment. The work order or maintenance request can betransmitted to a work order computer system, for example, or may betransmitted to a user device (e.g., associated with a maintenance orservice technician). In some embodiments, automated corrective actionincludes presenting an indication of the fault condition to a user(e.g., of user device 632). As an example, a notification or alert maybe generated and transmitted to the user's device as a text message, anemail, a voice call, a push notification, etc. In some embodiments, afault indication is presented on a user interface of a BMS system (e.g.,BMS 400).

In some embodiments, a diagnostic process may also be implemented todetermine a cause of the fault condition. The diagnostic process mayalso rely on the semantic site model, and in particular may rely on therelationships between BMS objects as defined in the semantic site model.For example, while one or more BMS object may be directly associatedwith a fault condition (e.g., the BMS object identified at step 906),additional BMS objects may also be identified that have some sort ofimpact on the detected fault condition. The semantic model may beanalyzed to identify, based on the BMS object relationships, additionalBMS objects that may be affected by the fault condition, or may havebeen at least partially responsible for causing the fault condition.

Referring now to FIGS. 10A-10C, an interface 1000 for viewing andmodifying a BMS object definition is shown, according to someembodiments. More specifically, interface 1000 may allow a user to editan object definition by adding, removing, or otherwise modifying one ormore point definitions associated with the object definition. In someembodiments, interface 1000 allows a user to select a model class foreach point definition associated with the object definition. Interface1000 may also allow a user to adjust point definition labels,identifiers, and other point definition parameters, as discussed below.Interface 1000 may be generated by user interface generator 618 andpresented to a user viewing user device 632, for example.

In the example shown in FIGS. 10A-10C, interface 1000 includes aplurality of point definitions associated with a particular BMS object,in this case a VAV unit (e.g., VAV units 116). Interface 1000 alsoincludes various parameters or information associated with each pointdefinition. Specifically, each point definition is shown with a pointlabel in a “Label” column 1002. The point labels in column 1002 may besemantic descriptions of points in a BMS that correspond to the variouspoint definitions. Each point definition is also shown to include anidentifier or a “short name,” listed in a “Short Name” column 1004, anda model class listed in a “Model Class” column 1006. Interface 1000 alsoincludes a “Search Criteria” column 1008 that includes a number ofsearch terms for each point definition. As shown in FIG. 10A, theexample VAV unit entity object includes three points definition. As anexample, a first point is shown as “Zone Air Temp,” with a short name of“ZN-T” and a model class of “ZONE_TEMPERATURE.”

A user may select an “edit” button 1010 to add, remove, or modify pointdefinition shown in interface 1000. Selecting button 1010 maydynamically modify interface 1000, as shown in FIG. 10B, to include avariety of control elements 1012. Control elements 1012 can include aplurality of button, icons, or other elements that facility adding,removing, or editing the various point definitions. For example, controlelements 1012 can include separate buttons to add and remove pointdefinitions, as well as buttons to navigate between the pointdefinitions presented in interface 1000. The user may select aparticular point definition, in this example “Zone Air Setpoint,” asshown in FIG. 10B, and may edit the selected point definition. Forexample, the user may edit the point definition's label, short name,search criteria, etc. The user may also assign a model class to theselected point definition.

When a user attempts to assign a model class to a selected pointdefinition, the user may be presented via a second interface forselecting a previously defined model class (e.g., a model class definedin the ontology data model, as described above). As shown in FIGS.11A-11B, for example, an example interface 1100 for selecting a modelclass may be presented. Interface 1100 may be presented as an overlay tointerface 1000 or a pop-up window, or in some cases may be a separateinterface that entirely replaces interface 1000. Interface 1100 mayinclude a list of all possible model classes that the user may select.In some embodiments, interface 1100 includes a “type” or an identifierfor each model class and a brief description of the model class.

As shown, a user may select an equipment type in a first graphicalelement 1102 of interface 1100. In some embodiments, element 1102 may bea text entry field, a drop-down menu, or any other suitable graphicalelement for identifying a particular equipment type. As discussed above,the equipment type may include any of a variety of equipment typesdefined in the ontology data model. In the example shown in FIG. 11A,the user has selected a VAV as the equipment type in element 1102. Thisselection corresponds to the type of equipment associated with theobject definition being viewed and/or modified in example FIGS. 10A-10C.

After selecting an equipment type (e.g., VAV), the user may select apoint purpose from a second graphical element 1104. Like element 1102,element 1104 may be a text entry field, a drop-down menu, or any othersuitable graphical element for identifying a point purpose. In someembodiments, element 1104 may not be populated until a particularequipment type is selected in element 1102. For example, element 1104may be a drop-down menu, and the particular point purpose selectionslisted in the drop-down menu may not be populated until an equipmenttype is selected. Accordingly, the point purpose may be related to theequipment type selected using element 1102. In the example shown in FIG.11B, the user has selected a point purpose of “Temperature”.

Once the user has selected an equipment type or has selected both anequipment type and a point purpose, the user may select a “Filter”button 1106 to filter the list of model classes. Filtering the list ofmodel classes may hide or remove model classes that do not correspond tothe select equipment type and/or point purpose. In other words, onlymodel classes that correspond to the equipment type and/or point purposeare populated in interface 1100. In the example of FIG. 11B, the userhas filtered the list to only include model classes associated withVAVs, and more particularly with temperature. Accordingly, the list ofmodel classes shown in FIG. 11B is shown to have been filtered to onlyinclude “Zone Temperature” and a Zone Temperature Setpoint.” The usermay then select a particular model class from the list and select a“Save” button 1110 in order to save the selected model class and assignit to the previously selected point definition. In some cases, the usermay select a “Cancel” button 1108 to return to interface 1000 withoutassigning a model class to a point definition.

Referring back to FIG. 10C, the user's selection of a particular modelclass via interface 1100 is shown to have been populated in interface1000, indicating that the user has assigned a model class to theselected point definition. In this example, the user has assigned amodel class “ZONE_SETPOINT” to a “Zone Air Setpoint” point definition.The user may subsequently choose to modify any of the other pointdefinitions shown. Once model classes are assigned to any of the pointdefinitions selected by the user, the user may select a “Save” button(e.g., one of control elements 1012) to save the changes. Alternatively,the user may select a “Cancel” button to disregard any changes (e.g.,assigned model classes).

Configuration of Exemplary Embodiments

The construction and arrangement of the systems and methods as shown inthe various exemplary embodiments are illustrative only. Although only afew embodiments have been described in detail in this disclosure, manymodifications are possible (e.g., variations in sizes, dimensions,structures, shapes and proportions of the various elements, values ofparameters, mounting arrangements, use of materials, colors,orientations, etc.). For example, the position of elements may bereversed or otherwise varied and the nature or number of discreteelements or positions may be altered or varied. Accordingly, all suchmodifications are intended to be included within the scope of thepresent disclosure. The order or sequence of any process or method stepsmay be varied or re-sequenced according to alternative embodiments.Other substitutions, modifications, changes, and omissions may be madein the design, operating conditions and arrangement of the exemplaryembodiments without departing from the scope of the present disclosure.

The present disclosure contemplates methods, systems and programproducts on any machine-readable media for accomplishing variousoperations. The embodiments of the present disclosure may be implementedusing existing computer processors, or by a special purpose computerprocessor for an appropriate system, incorporated for this or anotherpurpose, or by a hardwired system. Embodiments within the scope of thepresent disclosure include program products including machine-readablemedia for carrying or having machine-executable instructions or datastructures stored thereon. Such machine-readable media can be anyavailable media that can be accessed by a general purpose or specialpurpose computer or other machine with a processor. By way of example,such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROMor other optical disk storage, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to carry or storedesired program code in the form of machine-executable instructions ordata structures and which can be accessed by a general purpose orspecial purpose computer or other machine with a processor. Wheninformation is transferred or provided over a network or anothercommunications connection (either hardwired, wireless, or a combinationof hardwired or wireless) to a machine, the machine properly views theconnection as a machine-readable medium. Thus, any such connection isproperly termed a machine-readable medium. Combinations of the above arealso included within the scope of machine-readable media.Machine-executable instructions include, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing machines to perform a certain function orgroup of functions.

Although the figures show a specific order of method steps, the order ofthe steps may differ from what is depicted. Also two or more steps maybe performed concurrently or with partial concurrence. Such variationwill depend on the software and hardware systems chosen and on designerchoice. All such variations are within the scope of the disclosure.Likewise, software implementations could be accomplished with standardprogramming techniques with rule Based logic and other logic toaccomplish the various connection steps, processing steps, comparisonsteps and decision step.

What is claimed is:
 1. A building management system (BMS) comprising:one or more memory devices having instructions stored thereon that, whenexecuted by one or more processors, cause the one or more processors toperform operations comprising: obtaining a BMS ontology data modeldefining a plurality of BMS model classes and relationships between theBMS model classes; obtaining a plurality of BMS object definitionscomprising equipment definitions defining a plurality of different typesof equipment and point definitions defining a plurality of differenttypes of points; assigning a BMS model class to each of the plurality ofBMS object definitions, wherein the BMS model class is a semanticidentifier selected from the plurality of BMS model classes defined bythe BMS ontology data model; generating a semantic site model byclassifying a plurality of BMS objects associated with a building siteaccording to the BMS object definitions and the BMS model classesassigned thereto; and controlling building equipment using the semanticsite model.
 2. The BMS of claim 1, the operations further comprising:receiving a user input indicating one or more user-defined objectidentifiers associated with a first BMS object definition of theplurality of BMS object definitions; and wherein classifying theplurality of BMS objects comprises: identifying a subset of theplurality of BMS objects that satisfy at least one of the user-definedobject identifiers; and classifying the subset of the plurality of BMSobjects as the BMS model class assigned to the first BMS objectdefinition.
 3. The BMS of claim 1, the operations further comprising:analyzing configuration data for the BMS to identify a subset of theplurality of BMS objects that satisfy each of the plurality of BMSobject definitions; wherein each of the plurality of BMS objects areclassified as the BMS model class assigned to a corresponding BMS objectdefinition.
 4. The BMS of claim 1, wherein assigning the BMS model classto each of the plurality of BMS object definitions further comprises:receiving a user selection of the BMS model class for each of the BMSobject definitions; and assigning the BMS model class to each of theplurality of BMS object definitions based on the user selection.
 5. TheBMS of claim 1, wherein the BMS objects associated with the buildingsite include at least one of equipment objects representing specificbuilding equipment and point objects representing specific points in theBMS.
 6. The BMS of claim 1, wherein the BMS objects associated with thebuilding site include space objects representing specific spaces in thebuilding site and wherein the plurality of BMS object definitionsfurther comprise space definitions defining a plurality of differentspaces.
 7. The BMS of claim 1, the operations further comprising:obtaining a fault detection rule for the building site, the faultdetection rule comprising one or more fault criteria defined withoutreference to one or more particular BMS objects needed to evaluate thefault criteria; using the semantic site model to identify the particularBMS objects needed to evaluate the fault criteria; and detecting a faultcondition by evaluating the one or more fault criteria using dataassociated with the particular BMS objects.
 8. The BMS of claim 7,wherein evaluating the fault criteria comprises comparing a valueprovided by one or more of the particular BMS objects against athreshold.
 9. A method comprising: obtaining a BMS ontology data modeldefining a plurality of building management system (BMS) model classesand relationships between the BMS model classes; obtaining a pluralityof BMS object definitions comprising equipment definitions defining aplurality of different types of equipment and point definitions defininga plurality of different types of points; assigning a BMS model class toeach of the plurality of BMS object definitions, wherein the BMS modelclass is a semantic identifier selected from the plurality of BMS modelclasses defined by the BMS ontology data model; generating a semanticsite model by classifying a plurality of BMS objects associated with abuilding site according to the BMS object definitions and the BMS modelclasses assigned thereto; and controlling building equipment using thesemantic site model.
 10. The method of claim 9, further comprising:receiving a user input indicating one or more user-defined objectidentifiers associated with a first BMS object definition of theplurality of BMS object definitions; and wherein classifying theplurality of BMS objects comprises: identifying a subset of theplurality of BMS objects that satisfy at least one of the user-definedobject identifiers; and classifying the subset of the plurality of BMSobjects as the BMS model class corresponding to the first BMS objectdefinition.
 11. The method of claim 9, further comprising: analyzingconfiguration data for the BMS to identify a subset of the plurality ofBMS objects that satisfy each of the plurality of BMS objectdefinitions; wherein each of the plurality of BMS objects are classifiedas the BMS model class assigned to a corresponding BMS objectdefinition.
 12. The method of claim 9, wherein assigning the BMS modelclass to each of the plurality of BMS object definitions furthercomprises: receiving a user selection of the BMS model class for each ofthe BMS object definitions; and assigning the BMS model class to each ofthe plurality of BMS object definitions based on the user selection. 13.The method of claim 9, wherein the BMS objects associated with thebuilding site include at least one of equipment objects representinginstances of building equipment and point objects representing specificpoints in the BMS.
 14. The method of claim 9, wherein the BMS objectsassociated with the building site include space objects representingspecific spaces in the building site and wherein the plurality of BMSobject definitions further comprise space definitions defining aplurality of different spaces.
 15. The method of claim 9, furthercomprising: determining one or more fault detection rules for thebuilding site; detecting a trigger condition based on the one or morefault detection rules, the trigger condition indicating a fault and afirst BMS object associated with the fault; and identifying one or moreadditional BMS objects associated with the fault based on the semanticsite model.
 16. The method of claim 15, wherein the trigger conditioncomprises an indication that one or more parameters associated with thefirst BMS object exceed a threshold.
 17. The method of claim 15, whereindetermining one or more additional BMS objects associated with the faultcomprises: identifying a BMS model class associated with the first BMSobject; and identifying the one or more additional BMS objects based onthe relationships between the BMS model classes.
 18. A buildingmanagement system (BMS) comprising: one or more memory devices havinginstructions stored thereon that, when executed by one or moreprocessors, cause the one or more processors to perform operationscomprising: generating a semantic site model by classifying a pluralityof BMS objects associated with a building site according to a pluralityof BMS object definitions, each BMS object definition comprising anequipment definition defining a type of equipment and at least one pointdefinition defining a type of point, wherein each BMS object definitionis assigned a BMS model class selected from a BMS ontology data model;obtaining a fault detection rule for the building site, the faultdetection rule comprising one or more fault criteria defined withoutreference to one or more particular BMS objects needed to evaluate thefault criteria; using the semantic site model to identify the particularBMS objects needed to evaluate the fault criteria; detecting a faultcondition by evaluating the one or more fault criteria using dataassociated with the particular BMS objects; and initiating an automatedcorrective action in response to detecting the fault condition.
 19. TheBMS of claim 18, the operations further comprising: obtaining the BMSontology data model defining a plurality of BMS model classes andrelationships between the BMS model classes, wherein the BMS modelclasses are semantic identifiers selected from the plurality of BMSmodel classes defined by the BMS ontology data model.
 20. The BMS ofclaim 18, wherein the BMS objects associated with the building siteinclude space objects representing specific spaces in the building siteand wherein the plurality of BMS object definitions further comprisespace definitions defining a plurality of different spaces.